NVIDIA Jetson Nano Developer Kit (V3) (DEV-16271)

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Cue theme music…“Meet NVIDIA Jetson!” The latest addition the Jetson family, the NVIDIA® Jetson Nano™ Developer Kit (V3) delivers the performance to run modern … read more

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Could you please supply some more information on this product when compared to SKU: DFR0629 (DFRobot Jetson Nano). This Sparkfun kit obviously has two camera ports, what doesn’t it have to make it cheaper than the DFRobot version with only one camera port. Do they have the same fundamental specs? Why would I choose one over the other, except for the obvious stereo vision ability?



Cheers.

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I’d just like to know what “128-core Maxwell” means in real terms: how would this compare to a GTX 1060 graphics card? How would it compare to a Raspberry Pi 4? Are “core Maxwells” similar to CUDA cores?

The “128 core Maxwell” means that the underlying silicon architecture is NVidia’s Maxwell architecture, and there are 128 CUDA cores. The NVidia website has extensive information on the Jetson boards. Try here for example:

For comparisons with other SBCs, check some of the better YouTube channels such as “Explaining Computers” or “ETA Prime” to name a couple. I’m fairly confident that Explaining Computers has done a comparison of the Pi 4 and the Jetson.

I know NVidia’s graphics products can be used for deep learning.
I would like to know if one needs a PC or RPi connected to the DEV-16271 and the OS requirements.

That is does one write a program on a PC or RPi then send the number crunching deep learning algorithms to the DEV-16271 then the results from the DEV-16271 are sent back to the PC or RPi?

Does the OS matter - eg Win8, Win10, Linux.

Thank you,
Anthony of Sydney